Marking atomic events in sets of related texts

The notion of an event has been widely used in the computational linguistics literature as well as in information retrieval and various NLP applications, although with significant variance in what exactly an event is. We describe an empirical study aimed at developing an operational definition of an event at the atomic (sentence or predicate) level, and use our observations to create a system for detecting and prioritizing the atomic events described in a collection of documents. We report results from testing our system on several sets of related texts, including human assessments of the system's output and a comparison with information extraction techniques.